Artificial Intelligence (AI), big data, and in-memory processing use increasingly larger memory capacities. To meet this demand, in-memory deduplication systems (dedupe-DRAM) have been developed. Unfortunately, typical dedupe systems have some drawbacks. For example, the deduplication translation table may grow non-linearly as the size of the virtual memory grows. Additionally, deduplication operations typically result in some amplification of read and write latencies, that is, a single logical read or write may require multiple physical reads or writes, thereby reducing performance.